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A non-parametric approach of heteroskedasticity robust estimation of Vector-Autoregressive (VAR) models

Grobys, Klaus - In: Journal of finance and investment analysis 1 (2012) 1, pp. 55-67

This contribution studies the application of heteroskedasticity robust estimation of Vector-Autoregressive (VAR) models. VAR models have become one of the most applied models for the analysis of multivariate time series. Econometric standard software usually provides parameter estimators that...

Persistent link: https://www.econbiz.de/10009511728

A non-stationary approach for financial returns with nonparametric heteroscedasticity

Gürtler, Marc; Kreiß, Jens-Peter; Rauh, Ronald - 2009 - This Version: 2009-09-17

A non-stationary regression model for financial returns is examined theoretically in this paper. Volatility dynamics are modelled both exogenously and deterministic, captured by a nonparametric curve estimation on equidistant centered returns. We prove consistency and asymptotic normality of a...

Persistent link: https://www.econbiz.de/10009487234

Nonparametric Generalized Least Squares in Applied Regression Analysis

O'Hara, Michael E. - 2013

variants of heteroscedasticity robust standard error estimators (HRSEs) in an applied setting. Given myriad alternative HRSEs … various approaches to handling heteroscedasticity to data on professor rankings obtained from ratemyprofessor.com and find not … only heteroscedasticity to be prevalent but NPGLS and FGLS provide different insights and the statistical significance of …

Persistent link: https://www.econbiz.de/10013077989

A Multivariate Non-stationary Approach for Financial Returns with Nonparametric Heteroscedasticity

Gürtler, Marc - 2013

A non-stationary regression model for financial returns is examined theoretically. Volatility dynamics are modeled by nonparametric curve estimation on equidistant return vectors. We prove consistency and asymptotic normality of symmetric estimators and of one-sided estimators for variances and...

Persistent link: https://www.econbiz.de/10013095615

Application of the Scaling Functions to Nonparametric Regression

Manole, Daniel Sorin - 2007

For estimating regression function we can use many proceedings. In this paper, we have chosen to apply scaling functions to the estimation of regression functions. When one knows many bivariate date with the values of two variables, in the goal to express a correlation between the two variables...

Persistent link: https://www.econbiz.de/10014051848

Bayesian Nonparametric Sparse Seemingly Unrelated Regression Model (SUR)

Billio, Monica - 2017

Seemingly unrelated regression (SUR) models are useful in studying the interactions among different variables. In a high dimensional setting or when applied to large panel of time series, these models require a large number of parameters to be estimated and suffer of inferential problems.To...

Persistent link: https://www.econbiz.de/10012968298

Bayesian Nonparametric Conditional Copula Estimation of Twin Data

Dalla Valle, Luciana - 2017

Several studies on heritability in twins aim at understanding the different contribution of environmental and genetic factors to specific traits. Considering the National Merit Twin Study, our purpose is to correctly analyse the influence of the socioeconomic status on the relationship between...

Persistent link: https://www.econbiz.de/10012969727

Another Look at Single-Index Models Based on Series Estimation

Dong, Chaohua - 2016

In this paper, a semiparametric single-index model is investigated. The link function is allowed to be unbounded and has unbounded support that answers a pending issue in the literature. Meanwhile, the link function is treated as a point in an infinitely many dimensional function space which...

Persistent link: https://www.econbiz.de/10012980605

Generalized Additive Models for Pair-Copula Constructions

Vatter, Thibault - 2016

Pair-copula constructions are flexible models for the dependence in a random vector that have attracted a lot of interest in recent years. In this paper, we use generalized additive models to extend pair-copula constructions to allow for effects of covariates on the dependence parameters. We let...

Persistent link: https://www.econbiz.de/10012985827

Semiparametric Modelling and Estimation : A Selective Overview

Kristensen, Dennis - 2009

Semiparametric models are characterized by a finite- and infinite-dimensional (functional) component. As such they allow for added flexibility over fully parametric models, and at the same time estimators of parametric components can be developed that exhibit standard parametric convergence...

Persistent link: https://www.econbiz.de/10013156042